What Developers Need for Software Security Success
Most developers say they are willing to champion security and commit to higher standards of code quality and secure output, but they can’t do it without a lot of support, as well as a reworking of the traditional metrics by which they are often judged by their employers and organizations.
Govern AI-driven development before it ships
Measure AI-assisted risk, enforce secure coding policy at commit, and accelerate secure delivery across your SDLC.
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Forbes: A New Frontier: NSA Proposes “Security By Design” Considerations For AI Enablement
The cybersecurity industry, which has been advocating for “security by design” principles for more than a decade, stands in wide-eyed amazement at the risks posed by artificial intelligence (AI). As organizations rush to embrace AI enablement, a CISO’s most pressing priority is to avoid becoming a roadblock. However, without effective AI usage and governance, observability and traceability, organizations may be blindsided by their AI risk.
Techpartner.news: Secure Code Warrior introduces framework to govern AI use in software development
Secure Code Warrior has introduced the SCW AI Adoption Model, a framework designed to help organisations govern AI use in software development as the industry shifts from the traditional software development lifecycle (SDLC) toward what the company calls the Agentic Development Lifecycle (ADLC).
DevOps.com: Are LLMs Equally Good (or Bad) at Building Secure Software?
With many software engineering teams moving from AI coding assistants into full agentic AI code generation and increasing the amount of code they produce exponentially, ensuring the security of that code must be a top priority. The study produces practical guidance for organizations that are getting on board the AI-assisted or agentic code development train.
Secure AI-driven development before it ships
See developer risk, enforce policy, and prevent vulnerabilities across your software development lifecycle.
